Development of a battery pack supervisor algorithm using Rapid Control Prototyping

OData support
Supervisor:
Dr. Stumpf Péter Pál
Department of Automation and Applied Informatics

Nowadays, electric vehicles are increasingly popular in the automotive industry. One of the biggest and most important challenges of developing such vehicles is battery management; the key to achieving maximal battery lifespan, optimal charge and discharge profiles, and calculating the state of charge and state of health of the battery.

The history of electric vehicles is briefly elaborated in the Introduction, including the early days of electric automobiles, the spread of internal combustion engines, and the revitalized need for electrically powered cars in the present days.

This paper summarizes the numerous battery types used in the automotive industry, such as nickel metal hydride (NiMH) and lithium ion (Li-ion). Their advantages, drawbacks and basic working principles are discussed in the context of state-of-the-art battery technology. Moreover, the paper includes the summary of battery management systems and their basic functions.

The main task of this final project is to design the battery pack supervisor algorithm for a battery management system, using Rapid Control Prototyping. To achieve this goal, Li-ion cells are selected for a battery pack, and the conceptual design of the main parts of the battery hardware framework is carried out. The implementation of the battery management system uses MATLAB Simulink and the MotoHawk rapid control prototyping environment. The implemented software functions are the following: cell monitoring, cell protection, charge control, and cell balancing.

Finally, the implemented battery management functions are verified by rapid control prototyping tests on a physical battery pack, using the selected battery cells and a supervisory hardware framework. The cell monitoring and cell protection functions are verified by discharge tests. Oscilloscope measurements are also carried out for the balancing algorithm.

This final project was completed with professional guidance and resources given by AVL AUTÓKUT Engineering Ltd., the Engine and Powertrain Development Tech Center of AVL in Budapest.

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